Surface change detection in Xunwu County based on GEE and LandTrendr algorithms

Understanding land use change is crucial for exploring the impact of human activities on environmental evolution and the biosphere, and it provides essential support for scientific research and administrative decision-making. This study focuses on Xunwu County in Jiangxi Province, china, where Landsat data from 2000 to 2022 were processed using the Google Earth Engine (GEE) platform. The Random Forest algorithm and LandTrendr algorithm were applied for change detection, and a detailed analysis of long-term temporal changes in each land cover class was conducted. The results of the change detection reveal that the primary drivers of change in Xunwu County are human activities. The observed trends in the rate of change for different land cover types are consistent with policies such as the Grain-to-Green Program and urbanization, which demonstrates the applicability of the LandTrendr algorithm for detecting regional land surface changes.